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Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction
This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dim...
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| Publicado en: | Sensors (Basel) |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
MDPI
2017
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5422179/ https://ncbi.nlm.nih.gov/pubmed/28394270 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s17040818 |
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